warn skimage.viewer.warn(message, category=None, stacklevel=2) [source] A version of warnings.warn with a default stacklevel of 2.

vsobel skimage.filters.vsobel(*args, **kwargs) [source] Deprecated function. Use skimage.filters.sobel_v instead. Find the vertical edges of an image using the Sobel transform. Parameters: image : 2-D array Image to process mask : 2-D array, optional An optional mask to limit the application to a certain area. Note that pixels surrounding masked regions are also masked to prevent masked regions from affecting the result. Returns: output : 2-D array The absolute Sobel edge map. Note

vscharr skimage.filters.vscharr(*args, **kwargs) [source] Deprecated function. Use skimage.filters.scharr_v instead. Find the vertical edges of an image using the Scharr transform. Parameters: image : 2-D array Image to process mask : 2-D array, optional An optional mask to limit the application to a certain area. Note that pixels surrounding masked regions are also masked to prevent masked regions from affecting the result. Returns: output : 2-D array The absolute Scharr edge map.

vprewitt skimage.filters.vprewitt(*args, **kwargs) [source] Deprecated function. Use skimage.filters.prewitt_v instead. Find the vertical edges of an image using the Prewitt transform. Parameters: image : 2-D array Image to process. mask : 2-D array, optional An optional mask to limit the application to a certain area. Note that pixels surrounding masked regions are also masked to prevent masked regions from affecting the result. Returns: output : 2-D array The absolute Prewitt edge

view_as_windows skimage.util.view_as_windows(arr_in, window_shape, step=1) [source] Rolling window view of the input n-dimensional array. Windows are overlapping views of the input array, with adjacent windows shifted by a single row or column (or an index of a higher dimension). Parameters: arr_in : ndarray N-d input array. window_shape : integer or tuple of length arr_in.ndim Defines the shape of the elementary n-dimensional orthotope (better know as hyperrectangle [R383]) of the rolli

view_as_blocks skimage.util.view_as_blocks(arr_in, block_shape) [source] Block view of the input n-dimensional array (using re-striding). Blocks are non-overlapping views of the input array. Parameters: arr_in : ndarray N-d input array. block_shape : tuple The shape of the block. Each dimension must divide evenly into the corresponding dimensions of arr_in. Returns: arr_out : ndarray Block view of the input array. If arr_in is non-contiguous, a copy is made. Examples >>> i

Utility Functions img_as_float Convert an image to floating point format, with values in [0, 1]. img_as_uint Convert an image to unsigned integer format, with values in [0, 65535]. img_as_int Convert an image to signed integer format, with values in [-32768, 32767]. img_as_ubyte Convert an image to unsigned byte format, with values in [0, 255]. skimage.dtype_limits(image[, clip_negative]) Return intensity limits, i.e. skimage.img_as_bool(image[, force_copy]) Convert an image to boolean form

User Guide Getting started A crash course on NumPy for images NumPy indexing Color images Coordinate conventions Notes on array order A note on time Image data types and what they meanInput types Output types Image processing pipeline Rescaling intensity values Note about negative values References Image adjustment: transforming image contentColor manipulation Contrast and exposure I/O Plugin Infrastructure TutorialsImage Segmentation How to parallelize loops Getting help on using skimag

use_plugin skimage.data.use_plugin(name, kind=None) [source] Set the default plugin for a specified operation. The plugin will be loaded if it hasn’t been already. Parameters: name : str Name of plugin. kind : {‘imsave’, ‘imread’, ‘imshow’, ‘imread_collection’, ‘imshow_collection’}, optional Set the plugin for this function. By default, the plugin is set for all functions. See also available_plugins List of available plugins Examples To use Matplotlib as the default image reader, y

update_axes_image skimage.viewer.utils.update_axes_image(image_axes, image) [source] Update the image displayed by an image plot. This sets the image plot’s array and updates its shape appropriately Parameters: image_axes : matplotlib.image.AxesImage Image axes to update. image : array Image array.